kest

by larskarbo TypeScript Version: Current License: No License

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kandi X-RAY | kest Summary

kest is a TypeScript library. kest has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

kest

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Support

kest has a low active ecosystem.

It has 2 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

kest has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of kest is current.

Quality

kest has 0 bugs and 0 code smells.

Security

kest has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

kest code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

kest does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

kest releases are not available. You will need to build from source code and install.

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kest Key Features

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kest Examples and Code Snippets

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Community Discussions

Trending Discussions on kest

Trying to integrate an area under curve (AUC), error is "Error in match.fun(f): 'a1$iso' is not a function, character or symbol"

MySQL multiple if statements

Importing one dimensional dataset for Complete Spatial Randomness win spatstat

In what sense does K(r) [spatstat] become biased for point patterns with <15 points?

QUESTION

Trying to integrate an area under curve (AUC), error is "Error in match.fun(f): 'a1$iso' is not a function, character or symbol"

Asked 2020-Dec-02 at 00:32

For my project, I am trying to find a solution to a single value that will summarise the total degree of clustering in a landscape. My idea is to use the area under the curve between the Kiso value and the estimated Kpois to summarise the amount of clustering in a landscape. So using spatstat I first generate a landscape using the Matern Cluster Process.

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ANSWER

Answered 2020-Dec-02 at 00:32

Short answer:

Source https://stackoverflow.com/questions/65094903

QUESTION

MySQL multiple if statements

Asked 2020-Jul-09 at 12:55

I have a problem with MySQL query. I have a big query that selects from multiple tables and it works just fine. I would like to edit one small part of it.

This is the small part that I want to edit. This part works fine but I would like to add another if statement to it.

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ANSWER

Answered 2020-Jul-09 at 12:53

EDIT 1: Changed the query to match the bracket count but still no success.

After pretty formatting the problem becomes visible:

Source https://stackoverflow.com/questions/62814542

QUESTION

Importing one dimensional dataset for Complete Spatial Randomness win spatstat

Asked 2020-Feb-14 at 23:05

I have a set of one-dimensional data points (locations on a segment), and I would like to test for Complete Spatial randomness. I was planning to run Gest (nearest neighbor), Fest (empty space) and Kest (pairwise distances) functions on it.

I am not sure how I should import my data set though. I can use ppp by setting a second dimension to 0, e.g.:

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ANSWER

Answered 2020-Feb-14 at 23:05

It will be wrong to simply let y=0 for all your points and then proceed as if you had a point pattern in two dimensions. Your suggestion of using lpp is good. Regarding how to define the linnet and lpp try to look at my answer here.

I have considered making a small package to handle one dimensional patterns more easily in spatstat, but so far I have only started the package with a single function to make the definition of the appropriate lpp easier. If you feel adventurous you can install it from the GitHub repo via the remotes package:

Source https://stackoverflow.com/questions/60230338

QUESTION

In what sense does K(r) [spatstat] become biased for point patterns with <15 points?

Asked 2020-Feb-05 at 21:57

In the help file for the Kest function in spatstat there is a warning section stating:

"The estimator of K(r) is approximately unbiased for each fixed r. Bias increases with r and depends on the window geometry. For a rectangular window it is prudent to restrict the r values to a maximum of 1/4 of the smaller side length of the rectangle. Bias may become appreciable for point patterns consisting of fewer than 15 points."

I would like to know in what sense the estimator of K(r) becomes biased with increasing r and for point patterns with fewer than 15 points?

Any advice on this matter would be greatly appreciated!

I have read the book "Spatial point patterns" (Baddeley et al., 2015) but I can't seem to find the answer there (or in any other literature). I may of course have missed that section of the book, if so please let me know.

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ANSWER

Answered 2020-Feb-05 at 21:57

I don't know the historical facts about where n=15 comes from, but this is probably related to the fact that the estimate of K(r) is only ratio-unbiased. Typically what we can estimate directly is X(r) = lambda^2*K(r) where lambda is the the true intensity of the process. Then we use the estimate of this quantity, X_est(r) say, together with an estimate of lambda^2, lambda^2_est say, and then estimate K(r) as K_est(r) = X_est(r) / lambda^2_est. Thus the numerator and denominator are unbiased estimates of the right things, but the ratio isn't. The problem is worst when lambda^2 is poorly estimated, i.e., when we have few data points.

Source https://stackoverflow.com/questions/60074088

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